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Discover developers that match your project requirements.

No exact match for this specialty yet — here are related experts from our network.

Aditya P.
Available Now
Verified in SoftDoesAditya P.
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Aditya P.
Available Now
Aditya P.Verified in SoftDoes
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Aditya P.
Available Now
Aditya P.Verified in SoftDoes
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Andrea M.
Available Now
Verified in SoftDoesAndrea M.
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrea M.
Available Now
Andrea M.Verified in SoftDoes
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrea M.
Available Now
Andrea M.Verified in SoftDoes
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrii V.
Available Now
Verified in SoftDoesAndrii V.
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Andrii V.
Available Now
Andrii V.Verified in SoftDoes
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Andrii V.
Available Now
Andrii V.Verified in SoftDoes
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Boris S.
Available Now
Verified in SoftDoesBoris S.
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Boris S.
Available Now
Boris S.Verified in SoftDoes
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Boris S.
Available Now
Boris S.Verified in SoftDoes
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Eugene M.
Available Now
Verified in SoftDoesEugene M.
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Eugene M.
Available Now
Eugene M.Verified in SoftDoes
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Eugene M.
Available Now
Eugene M.Verified in SoftDoes
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Hripsime S.
Available Now
Verified in SoftDoesHripsime S.
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Hripsime S.
Available Now
Hripsime S.Verified in SoftDoes
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Hripsime S.
Available Now
Hripsime S.Verified in SoftDoes
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Mario J.
Available Now
Verified in SoftDoesMario J.
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Mario J.
Available Now
Mario J.Verified in SoftDoes
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Mario J.
Available Now
Mario J.Verified in SoftDoes
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Raphael O.
Available Now
Verified in SoftDoesRaphael O.
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Raphael O.
Available Now
Raphael O.Verified in SoftDoes
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Raphael O.
Available Now
Raphael O.Verified in SoftDoes
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Santiago G.
Available Now
Verified in SoftDoesSantiago G.
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Santiago G.
Available Now
Santiago G.Verified in SoftDoes
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Santiago G.
Available Now
Santiago G.Verified in SoftDoes
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Thierry M.
Available Now
Verified in SoftDoesThierry M.
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thierry M.
Available Now
Thierry M.Verified in SoftDoes
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thierry M.
Available Now
Thierry M.Verified in SoftDoes
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thomas S.
Available Now
Verified in SoftDoesThomas S.
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Thomas S.
Available Now
Thomas S.Verified in SoftDoes
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Thomas S.
Available Now
Thomas S.Verified in SoftDoes
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Tzechung K.
Available Now
Verified in SoftDoesTzechung K.
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

Tzechung K.
Available Now
Tzechung K.Verified in SoftDoes
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

Tzechung K.
Available Now
Tzechung K.Verified in SoftDoes
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

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What our Marketing Managers can build

Not sure which engagement model fits?

SoftDoes takes full ownership of delivery, combining project management, engineering, design, and QA into one accountable team focused on successful outcomes.

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RIGHT expert, FASTER

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How to hire a Marketing Manager

01
BROWSE PROFILESRIGHT NOW

Fill out a short form and see who's on the bench. Real profiles, verified histories.

02
Interview1-3 DAYS

Tell us what you need. We propose two or three candidates from the bench; you interview them directly.

03
OnboardWEEK ONE

Your engineer starts on your project. Contract, payments, and the guarantee run through us.

US VS. THE DATABASE

Time to Start
Talent Quality
Technical Vetting
Flexibility
Operational Overhead
Cost Efficiency
cursor
<SoftDoes>
Time to Start
1-2 weeks
Talent Quality
Senior-only engineers
Technical Vetting
Multi-stage screening
Flexibility
Scale up or down anytime
Operational Overhead
As managed as you want
Cost Efficiency
Competitive, fee-free
Talent Marketplaces
Time to Start
1-3 months
Talent Quality
Mixed experience levels
Technical Vetting
One screen, then gone
Flexibility
Contract restrictions
Operational Overhead
Partially managed
Cost Efficiency
Agency markup
In-House Hiring
Time to Start
2-6 months
Talent Quality
Depends on market
Technical Vetting
Internal responsibility
Flexibility
Long-term commitment
Operational Overhead
Fully internal
Cost Efficiency
Highest total cost

Frequently Asked Questions

Everything you need to know about deploying, scaling, and securing your neural agents with SoftDoes. Can’t find an answer?

How long does it take to hire a Marketing Manager through SoftDoes?

For most engagements, our prescreened talent network and structured vetting process mean you can have a qualified, deployed marketing manager within two to four weeks. In highly specialized verticals such as healthcare or finance, where compliance expertise and technical skills narrow the candidate pool, the timeline may extend slightly. The key difference is that we eliminate the months of sourcing, screening, and back and forth that define traditional job search processes. Our focused pipeline consistently reduces time to hire compared to conventional recruitment, so you start seeing results faster without sacrificing candidate quality.

What does it cost to hire a Marketing Manager?

Cost depends on geography, seniority, engagement model, and domain specialization. For senior marketing manager roles in North American tech and regulated industries, base compensation typically ranges from $130K to $200K plus performance incentives. When engaging through a partner network like SoftDoes, costs may shift based on overhead, tooling, and engagement structure, but you also eliminate the hidden costs of a bad hire: turnover, ramp up delays, lost revenue, and wasted engineering cycles. We work with you to align investment with your actual marketing needs and budget realities, ensuring you pay for outcomes rather than overhead.

What engagement models are available (dedicated hire, pod, contract)?

SoftDoes offers three primary engagement models. A dedicated hire gives you a full time marketing manager embedded with your existing team, operating as a seamless extension of your organization. A pod model provides a small, cross functional unit (for example, a marketing manager paired with a data analyst and a content strategist) that can execute marketing strategies end to end. A contract or interim engagement is ideal when you need strategic planning and execution for a defined project scope, a product launch window, or a transitional period. Each model offers distinct tradeoffs in control, speed, and overhead, and we help you choose based on your product roadmap and business goals.

How do you ensure time zone alignment with a Marketing Manager?

For remote senior hires, we require a minimum of four overlapping working hours with your core team, with agreed upon core hours established before engagement begins. We also set clear asynchronous communication protocols and regular meeting rhythms so that collaboration remains tight even across geographies. Our North America focused delivery model means the vast majority of our marketing professionals are already aligned with US and Canadian business hours, minimizing friction and ensuring your digital marketing efforts never stall waiting for a response.

How does SoftDoes technically vet a Marketing Manager?

Our vetting process goes far beyond resume review. Candidates complete live problem solving exercises using real world scenarios (budget reallocation under constraints, channel prioritization, data analysis challenges). They perform architecture reviews of martech stacks, identifying gaps in tracking, attribution, or data pipelines. We assess communication under pressure through cross functional interview panels that include engineering and product leadership. Finally, we evaluate work samples: actual campaign dashboards, analytics reports, and strategic planning documents, not hypothetical case studies. Structured interviews with standardized scorecards ensure we compare candidates on substance, not charisma.

What happens if the Marketing Manager isn't the right fit, or I need to scale up or down?

Our zero risk replacement guarantee means that if the marketing manager does not meet your performance standards or align with your team dynamics, we replace them at no additional cost. We also build in a structured 90 day performance review, evaluating against the milestones established during onboarding. If your product roadmap shifts and you need to scale up, we can deploy additional talent from our network rapidly. If you need to scale down, there are no long term contracts locking you in. The goal is to ensure you are completely satisfied with both the talent and the flexibility to adapt as your company's products and market demands evolve.

The Executive Guide to Hiring a Marketing Manager

A single bad marketing manager hire can quietly drain six figures in wasted salary, lost pipeline velocity, and delayed product launches before anyone flags the problem. A slow hiring process bleeds even more: every open week is a week your competitors capture market share you will never recover. This playbook gives you a field tested strategy to define, vet, and onboard top tier marketing manager talent, built from lessons learned across hundreds of enterprise engagements where the margin for error was zero.

What Actually Separates Strategic Talent from Expensive Order Takers

The True Scope of a Senior Marketing Manager's Daily Operating Reality

Most manager job descriptions floating around LinkedIn read like a checklist of tools and channels. That is exactly how you end up with an expensive coordinator instead of a strategic owner. The right marketing manager operates as a system architect for revenue growth. Here is what that looks like in practice:

  • Full funnel ownership, not channel babysitting. They own the entire demand pipeline from market research and product positioning through paid acquisition, content marketing, lead generation, and retention. They do not wait for someone else to hand them a brief.
  • Measurement infrastructure design. They build or audit attribution models (multi touch, not last click fairy tales), define key performance indicators, and ensure dashboards reflect reality. They can speak fluently about customer acquisition cost, lifetime value, ROAS, and pipeline velocity.
  • Budget and tradeoff management. They make hard calls: when to shift spend from search engine optimization to Google Ads, when to kill a campaign that looks good on vanity metrics but delivers unqualified leads, and when to invest in long term brand building over short term performance.
  • Cross functional leadership. A digital marketing manager who cannot work shoulder to shoulder with engineering, product, UX, and data teams is a liability. They must understand sprint cycles, API constraints, backlog priorities, and data pipeline limitations to ensure smooth execution.
  • Agile experimentation. Growth and experimentation frameworks are crucial for customer acquisition and retention. They run structured A/B tests, iterate based on data analytics, and kill what does not work without ego.
  • Technical fluency that bridges marketing and engineering. In regulated industries or companies running AI and cloud infrastructure, this means understanding compliance requirements, data architecture, and digital transformation realities. Technical fluency is needed to bridge marketing and engineering teams effectively.

A data driven mindset is essential for digital marketing product managers. Without it, you are paying senior rates for someone who executes marketing strategies by gut feel.

The Financial and Operational Case for Getting This Hire Right

Hiring a digital marketing product manager requires a blend of technical and marketing skills. When you land the right hire, these are the concrete ROI vectors that justify the investment:

  • Reduced technical debt and martech overhead. An experienced marketing manager who understands your CRM software, analytics stack, and data pipelines can identify redundant tools, eliminate integration friction, and cut subscription costs, sometimes saving tens of thousands annually.
  • Faster time to market for product launches. Tight coordination between marketing and engineering means new features and products generate revenue sooner. Digital product managers oversee the entire product life cycle, and the marketing counterpart ensures the go to market engine is ready the moment engineering ships.
  • Optimized acquisition cost and improved lifetime value. Using attribution models, performance metrics, and structured experimentation, they lower CAC, improve ROAS, and raise LTV. Marketing managers improve ROI through targeted, data driven campaigns.
  • Risk mitigation in regulated verticals. In healthcare, finance, or education, bad messaging or non compliant data handling creates legal exposure. A senior marketing manager with domain expertise prevents costly missteps before they happen.

By 2028, the digital economy will account for 17% of global GDP. Digital goods revenue is projected to grow from $124.3 billion in 2025 to $416 billion by 2030. Companies without strong digital product leadership risk falling behind. The demand for skilled marketing managers has surged in recent years precisely because the stakes have never been higher.

Preparing to Search: What Most Executives Skip and Then Regret

Auditing Your Technical Constraints Before You Write a Single Job Description

Before you post a role or call a recruiter, you need to understand what you are actually buying. Most failed hires trace back to a poorly defined problem, not a bad candidate.

Architecture and Debt Audit

What problem must this hire solve first? Audit your current martech stack. Do you have systems for tracking user behavior and campaign attribution, or are your marketing efforts running blind? Are there data silos where marketing cannot access raw analytics? If your ability to measure impact or deploy personalized campaigns is fundamentally broken, hiring a brilliant strategist without fixing infrastructure is like hiring a Formula 1 driver and handing them a go kart.

Team Dynamics and Autonomy Level

Where does this person sit? Embedded with the product and engineering team? Leading a dedicated marketing team? Solo contributor influencing cross functional teams? The autonomy level you define directly determines the seniority you need. If you expect ownership of marketing strategy and budget decisions, you need someone with strong leadership and team management skills, not someone who needs approval on every email.

Deployment Model Dynamics

The traditional in house FTE model brings familiarity but also friction: long hiring timelines, onboarding overhead, and risk if the fit fails. Vetted dedicated remote talent through a partner network offers speed and flexibility, but demands clear communication protocols and time zone alignment. Understand your tradeoffs before you commit to a model.

Engineering the Ideal Candidate Profile, Not Another Generic Job Spec

A well crafted job description is your single most powerful screening tool. A clear job description attracts the right candidates. A vague one attracts everyone and qualifies no one. Build your profile around four essential components:

  • Core outcome and mission. Define what this person must deliver in the first 90 days. Is it launching a product into a new market? Revamping a legacy funnel? Entering a regulated vertical? A marketing manager typically requires a bachelor's degree in marketing, but credentials matter far less than mission alignment. Hiring should focus on outcomes rather than responsibilities in resumes.
  • Technical stack reality. Specify your actual environment: Google Analytics (GA4), your CRM platform, front end frameworks, cloud infrastructure, AI/ML pipelines. Do not list aspirational tools. List what they will use on day one.
  • Decision making authority. Will they make budget calls? Choose digital channels? Own product marketing strategy? Clear scope and expectations should be defined when hiring a digital marketing product manager. If you hire for seniority but restrict authority, you lose impact and morale simultaneously.
  • Growth trajectory and leadership path. What is the step to Director or VP? How large is the team and budget? Ambitious marketing professionals want clarity on career, influence, and project scope. Include a job summary to highlight the role's purpose. Specify job requirements such as travel availability or flexible hours, and highlight benefits like competitive salaries and career development.
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Vetting and Onboarding: Where Most Hiring Processes Quietly Fail

A Vetting Framework Built for Signal, Not Theater

Sourcing Reality

Traditional recruiters often present resumes that look perfect on paper but collapse under scrutiny. They optimize for volume, not depth. Pure job search platforms generate noise. The alternative: prescreened engineering led talent networks where candidates have already been evaluated for technical expertise and cross functional capability. SoftDoes maintains exactly this kind of vetted talent pool, built specifically for companies that need marketing managers who speak engineering fluently.

Structured interviews improve candidate comparison and reduce first impression bias. Use standardized scorecards, ensure multiple reviewers from engineering, product, and marketing, and keep the process moving. Long, opaque hiring pipelines cause top candidates to drop off.

Technical Evaluation Pipeline

Forget trivia questions about the latest social media management platform. Here is how to identify strong candidates who can actually perform:

  • Live problem solving over trivia. Present a real scenario: you have three channels (SEO, paid media, content marketing), and budget is cut by 30%. Where do you reallocate spend and why? This tests strategic planning, tradeoff analysis, and business acumen in minutes.
  • Real world architecture review. Have the candidate review your current martech stack (or a sanitized version) and critique gaps in tracking, attribution, or data pipelines. Can they identify opportunities for improvement? Do they understand the difference between correlation and actual lift?
  • Communication under pressure. Senior roles require alignment with engineering, product, and leadership. Test clarity, narrative framing, and the ability to explain constraints and tradeoffs to a non marketing audience. Cross functional leadership is important in influencing without direct authority.
  • Cross functional culture fit. Include your engineering lead and product manager in the interview. Does the candidate understand sprint cycles, data availability, compliance constraints? Or do they operate in a marketing silo?

Hiring processes should include practical case studies to assess problem solving skills. Use work samples, real campaign outcomes, and dashboard walkthroughs instead of hypothetical theory. Candidates should demonstrate familiarity with key performance indicators and performance dashboards from actual experience.

The First 90 Days: A Frictionless Ramp Up Protocol That Protects Your Investment

To get ROI fast and validate fit, structure the onboarding around clear milestones:

  • Days 1 through 30: Audit and align. The new hire audits existing digital channels, data stack, campaign history, and customer insights. They align on performance metrics, set up dashboards, meet cross functional partners, and identify quick wins. Marketing managers analyze market trends and customer data to find immediate opportunities. They should surface what is working, what is broken, and what is missing.
  • Days 31 through 60: Execute and prove. Launch or optimize one to two growth experiments. Begin ownership of key marketing channels. Show measurable improvements: CAC down, funnel velocity up, qualified leads increasing. Introduce process improvements in coordination with engineering and data teams. This is where you validate whether they can execute marketing strategies or just talk about them.
  • Days 61 through 90: Own and scale. Own the go to market plan for a product or feature launch. Present a roadmap for upcoming quarters. Establish regular reporting and constructive feedback rhythms with the existing team and leadership. If they are leading others, begin mentoring or expanding the marketing team. Marketing managers oversee campaigns across social media and traditional channels, and by day 90, they should be running this machine independently.

Making the Call: Separating Contenders from Pretenders

The Interview Signals That Predict Real World Performance

After years of watching hires succeed and fail across enterprise systems, these are the signals that actually matter.

Red Flags:

  • Tool obsession over problem solving. The candidate lists every platform from Google Ads to the latest social media marketing tool but cannot describe a single tradeoff, constraint, or strategic decision they made. Digital capabilities mean nothing without the judgment to deploy them.
  • Inability to discuss past failures. Senior hires must be able to articulate where they were wrong, what they learned, and what they would do differently. Avoidance signals either inexperience or dishonesty.
  • Weak data judgment. If they cannot explain the difference between a vanity metric and a real KPI, or cannot walk through how they analyze market trends and customer acquisition cost, they are not ready for a senior role. Analyzing customer acquisition cost and return on investment is essential for data fluency.
  • Silo mentality. No experience working with engineering, product, or data teams. Too much "marketing only" thinking. In a modern company, this creates friction and blind spots that slow the entire team.

Green Flags:

  • Pragmatic tradeoff analysis. They can defend decisions like reducing spend in one channel even if nominal cost per lead is low but lead quality is poor. They think in terms of business objectives, not just marketing goals.
  • Focus on system and data integrity. They mention tracking issues, data quality, pipeline reliability. They understand "garbage in, garbage out" and prioritize measurement infrastructure. A digital marketing product manager should understand product lifecycle and digital marketing channels at this level of depth.
  • Proactive risk and edge case identification. They flag compliance risks, churn patterns, customer segmentation misalignments, or market shifts before you ask. Marketing managers help businesses stay competitive by monitoring market trends and customer feedback.
  • Outcome timelines with receipts. They can talk about what they delivered in 30, 60, and 90 days, which performance metrics moved, and what they did when something did not work. Effective marketing managers create targeted, data driven campaigns, and the best ones can prove it.

Why Executives Choose SoftDoes as Their Strategic Hiring Partner

SoftDoes is not a staffing agency. We are a North America focused custom software engineering, data, and AI partner that deploys senior marketing talent who speak engineering fluently. That distinction matters because:

  • Battle tested senior talent. Every marketing manager and product marketing manager in our network has been vetted through the technical evaluation pipeline described above, not just a resume screen and a culture chat. You get marketing professionals with a thorough understanding of data analytics, cloud infrastructure, and digital marketing strategy.
  • Engineering led delivery oversight. We do not hand you a freelancer and disappear. Our architects review technical foundation, ensure measurement infrastructure is in place from day one, and monitor delivery quality. This is the difference between managed outcomes and unmanaged hope.
  • Rapid deployment, not months of waiting. While traditional hiring cycles run six to eight weeks (or longer in regulated verticals), our prescreened network means you can deploy a qualified digital marketer in a fraction of that time.
  • Flexible scaling. Dedicated hire, pod model, or contract engagement. Scale up when your product roadmap demands it, scale down when it does not. No long term lock in.
  • Zero risk replacement guarantee. If the fit is not right, we replace the hire. Traditional recruitment offers you a refund policy and a "good luck." We offer continuity. Consistent brand messaging builds trust and loyalty among audiences, and consistent talent delivery builds trust with your leadership team.

Your Next Step: Stop Losing Time and Start Building Momentum

Every week without the right marketing manager in place is a week of lost pipeline, delayed launches, and competitor advantage you are handing away for free. Hiring a marketing manager can generate qualified leads for sales teams, accelerate business growth, and align your marketing efforts with your company's goals.

If you are ready to find marketing managers who deliver measurable outcomes, not just polished resumes, book a technical discovery session with our architects. We will audit your current constraints, define the ideal profile together, and match you with battle tested talent that fits your stack, your industry, and your ambition.

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